Toward Optimized IoT Sensor Networks for Smart Cities: Centrality-Aware Position-Based Occlusion-Driven and Role Dynamics Solutions for Clustering and Routing

This paper introduces a novel clustering and routing protocol for Internet of Things (IoT) sensor networks aimed at reducing energy consumption and extending the lifespan, a critical requirement for smart cities. The proposed protocol demonstrates significant potential in diverse IoT applications, including smart logistics parks, smart medical centers, smart factory zones, smart universities, and smart cities. By ensuring energy-efficient, long-lasting sensor networks, the proposed protocol supports continuous real-time data collection and monitoring, enabling cities to achieve sustainability goals, enhance urban resilience, and improve operational efficiency. The protocol dynamically divides the sensing area into equal-sized Hexagonal Clusters (HCs), adapting to variations in network size, Sensor Node (SN) count, and their distribution. Each HC is managed by a Cluster Head (CH), selected using the Marine Predators Algorithm (MPA), which excels in optimization tasks. The MPA algorithm determines the optimal CH by evaluating four key cluster fitness function parameters: the SNs’ distance to the sink, the Average Scale of Building Occlusions (ASBO), the SN centrality, and the CH role count. Furthermore, our proposed protocol incorporates an innovative relay cost function for the purpose of data forwarding, where CHs transmit data hop-by-hop to the sink, selecting relay nodes based on their role count, distance from the sink, ASBO, and distance from other CHs. Simulation results validate the protocol’s effectiveness, demonstrating its superior performance in extending network lifespan, increasing throughput, reducing average delay, and conserving energy. The proposed protocol outperforms existing protocols, establishing a new benchmark for energy-efficient clustering and routing in IoT applications.